Evidence map›Paper›PMID 40615496›Full record

ArticleNPJ digital medicine2025

AI assistance enhances histopathologic distinction between sebaceous and squamous cell carcinoma of the eyelid.

Jialu Geng, Kai Zhang, Li Dong, Shiqi Hui, Qian Zhang, Zhixi Li, Ruiheng Zhang, Xue Jiang, Mingyang Wang, Shuantao Sun and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Jialu Geng *Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology＆Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Key Laboratory of Intelligent Diagnosis, Treatment and Prevention of Blinding Eye Diseases, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
Kai Zhang *Gyenno Science Co. Ltd., Shenzhen, China.
Li Dong *Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology＆Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Key Laboratory of Intelligent Diagnosis, Treatment and Prevention of Blinding Eye Diseases, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
Shiqi Hui *Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology＆Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Key Laboratory of Intelligent Diagnosis, Treatment and Prevention of Blinding Eye Diseases, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
Qian Zhang *Department of Pathology, Beijing Tongren Hospital Affiliated with Capital Medical University, Beijing Key Laboratory of Head and Neck Pathology Diagnosis, Beijing, China.
Zhixi LiState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China.
Ruiheng ZhangBeijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology＆Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Key Laboratory of Intelligent Diagnosis, Treatment and Prevention of Blinding Eye Diseases, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
Xue JiangBeijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology＆Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Key Laboratory of Intelligent Diagnosis, Treatment and Prevention of Blinding Eye Diseases, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
Mingyang WangBeijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology＆Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Key Laboratory of Intelligent Diagnosis, Treatment and Prevention of Blinding Eye Diseases, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
Shuantao SunSenior Department of Ophthalmology, The Third Medical Center of Chinese PLA General Hospital, Beijing, China.
Hong ZhangDepartment of Pathology, Beijing Tongren Hospital Affiliated with Capital Medical University, Beijing Key Laboratory of Head and Neck Pathology Diagnosis, Beijing, China.
Yunyun YangDepartment of Pathology, Beijing Tongren Hospital Affiliated with Capital Medical University, Beijing Key Laboratory of Head and Neck Pathology Diagnosis, Beijing, China.
Xinji YangSenior Department of Ophthalmology, The Third Medical Center of Chinese PLA General Hospital, Beijing, China. yangxinji68@sina.com.
Yingshi PiaoDepartment of Pathology, Beijing Tongren Hospital Affiliated with Capital Medical University, Beijing Key Laboratory of Head and Neck Pathology Diagnosis, Beijing, China. piaoyingshi2013@163.com.
Dongmei LiBeijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology＆Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Key Laboratory of Intelligent Diagnosis, Treatment and Prevention of Blinding Eye Diseases, Beijing Tongren Hospital, Capital Medical University, Beijing, China. ldmlily@x263.net.

Funding

National Natural Science Foundation of China 82071005the Sanming Project of Medicine in Shenzhen SZSM202311018
6 · The paper itself

Abstract

Sebaceous gland carcinoma (SGC) and some poorly differentiated squamous cell carcinomas (SC) of the eyelid may have overlapping clinical and histopathologic features, leading to potential misdiagnosis and delayed treatment. The authors developed a deep learning (DL)-based pathological analysis framework to classify SGC and SC automatically. In total, 282 whole slide images (WSIs) were used for training, validating and inner testing the DL framework and 36 WSIs were obtained from another hospital as an external testing dataset. In WSI level, the diagnostic accuracy of SGC and SC achieved 84.85% and 75.12%, respectively, in the internal testing set and reached 22.22% and 77.78%, respectively, in the external testing set. The accuracy of the pathologists could be improved with the AI framework (60.0 ± 9.8% vs. 76.8 ± 9.6%). This AI-based automatic pathological diagnostic framework achieved the performance of a well-experienced pathologist and can assist pathologists in making diagnoses more accurately, especially for non-ophthalmic pathologists.

Identifiers

PMID40615496
PMCPMC12227637

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